Calendar Details

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Tuesday, September 30

NOTE TIME CHANGE:
Bioimaging Data to Drive Mathematical Models
of Tumor Growth and Treatment Response

Tom Yankeelov, Vanderbilt University, Nashville, Tenn.
Computational Sciences and Engineering Division Seminar
11:00 AM, Research Office Building (5700), Room L-204
Contact: ( scottar@ornl.gov), 865.241.0331

Abstract

Current mathematical models of tumor growth rely on knowledge of molecular level data that is normally quite difficult or even impossible to measure in an intact living system (e.g., metrics of chemotaxis, haptotaxis, growth factor gradients, etc.). Thus, the general limitation of these models is that they are almost uniformly driven by parameters that can be measured only by highly invasive methods (surgery and/or animal sacrifice) or idealized (in vitro) systems. In contrast, mathematical models of tumor growth that can be parameterized and driven by data obtained from noninvasive imaging experiments do not have this limitation. In this seminar we will discuss how relevant mathematical models of tumor growth can, in principle, be constructed that are driven by non-invasive imaging data. Towards this end, we will provide a review of common cancer imaging methods and present an example of how a mathematical model can be driven by such data.

Dr. Thomas Yankeelov is an Assistant Professor of Radiology, Physics, Biomedical Engineering, and Cancer Biology at Vanderbilt University. He received an M.A. in Applied Mathematics and an M.S. in Physics from Indiana University in 1998 and 2000, respectively. His doctorate is from SUNY at Stony Brook where he completed his Dissertation at Brookhaven National Laboratory in 2003. He has since published 24 peer reviewed journal papers, over 50 conference proceedings, and given over 35 seminars on quantitative imaging of cancer. Dr. Yankeelov has been teaching graduate courses in Imaging Science for the past four years while at Vanderbilt University. He and his colleagues have developed and extensively used many of the techniques described in this course.